Overview

Dataset statistics

Number of variables10
Number of observations306145
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.4 MiB
Average record size in memory80.0 B

Variable types

Numeric10

Alerts

u is highly correlated with g and 6 other fieldsHigh correlation
g is highly correlated with u and 7 other fieldsHigh correlation
r is highly correlated with u and 7 other fieldsHigh correlation
i is highly correlated with u and 7 other fieldsHigh correlation
z is highly correlated with u and 7 other fieldsHigh correlation
uErr is highly correlated with u and 7 other fieldsHigh correlation
gErr is highly correlated with u and 8 other fieldsHigh correlation
rErr is highly correlated with u and 8 other fieldsHigh correlation
iErr is highly correlated with g and 7 other fieldsHigh correlation
zErr is highly correlated with gErr and 2 other fieldsHigh correlation
u is highly correlated with g and 6 other fieldsHigh correlation
g is highly correlated with u and 6 other fieldsHigh correlation
r is highly correlated with u and 7 other fieldsHigh correlation
i is highly correlated with u and 7 other fieldsHigh correlation
z is highly correlated with u and 7 other fieldsHigh correlation
uErr is highly correlated with u and 7 other fieldsHigh correlation
gErr is highly correlated with u and 8 other fieldsHigh correlation
rErr is highly correlated with u and 8 other fieldsHigh correlation
iErr is highly correlated with r and 6 other fieldsHigh correlation
zErr is highly correlated with gErr and 2 other fieldsHigh correlation
u is highly correlated with g and 5 other fieldsHigh correlation
g is highly correlated with u and 6 other fieldsHigh correlation
r is highly correlated with u and 6 other fieldsHigh correlation
i is highly correlated with u and 6 other fieldsHigh correlation
z is highly correlated with u and 6 other fieldsHigh correlation
uErr is highly correlated with u and 6 other fieldsHigh correlation
gErr is highly correlated with u and 7 other fieldsHigh correlation
rErr is highly correlated with g and 7 other fieldsHigh correlation
iErr is highly correlated with gErr and 2 other fieldsHigh correlation
zErr is highly correlated with rErr and 1 other fieldsHigh correlation
u is highly correlated with g and 6 other fieldsHigh correlation
g is highly correlated with u and 7 other fieldsHigh correlation
r is highly correlated with u and 8 other fieldsHigh correlation
i is highly correlated with u and 8 other fieldsHigh correlation
z is highly correlated with u and 8 other fieldsHigh correlation
uErr is highly correlated with u and 7 other fieldsHigh correlation
gErr is highly correlated with u and 8 other fieldsHigh correlation
rErr is highly correlated with u and 8 other fieldsHigh correlation
iErr is highly correlated with g and 7 other fieldsHigh correlation
zErr is highly correlated with r and 5 other fieldsHigh correlation
uErr has unique values Unique
gErr has unique values Unique
rErr has unique values Unique
iErr has unique values Unique
zErr has unique values Unique

Reproduction

Analysis started2022-02-27 19:48:03.712804
Analysis finished2022-02-27 19:48:29.202488
Duration25.49 seconds
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

u
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct286447
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.450424162
Minimum4.14008053
Maximum4.715880085
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-02-27T16:48:29.250179image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum4.14008053
5-th percentile4.298432906
Q14.394878337
median4.458346435
Q34.505397268
95-th percentile4.579030693
Maximum4.715880085
Range0.5757995554
Interquartile range (IQR)0.1105189316

Descriptive statistics

Standard deviation0.08727256171
Coefficient of variation (CV)0.01960994245
Kurtosis0.7369244066
Mean4.450424162
Median Absolute Deviation (MAD)0.05386319209
Skewness-0.2068753038
Sum1362475.105
Variance0.007616500028
MonotonicityNot monotonic
2022-02-27T16:48:29.339044image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.4471139815
 
< 0.1%
4.4484542675
 
< 0.1%
4.4767289045
 
< 0.1%
4.4700871324
 
< 0.1%
4.4475834944
 
< 0.1%
4.4933365784
 
< 0.1%
4.5078475274
 
< 0.1%
4.3655855354
 
< 0.1%
4.4675019334
 
< 0.1%
4.4360504074
 
< 0.1%
Other values (286437)306102
> 99.9%
ValueCountFrequency (%)
4.140080531
< 0.1%
4.1401112961
< 0.1%
4.1401952441
< 0.1%
4.1402525161
< 0.1%
4.140291951
< 0.1%
4.1404635841
< 0.1%
4.1404702921
< 0.1%
4.1404742181
< 0.1%
4.1404834621
< 0.1%
4.140574261
< 0.1%
ValueCountFrequency (%)
4.7158800851
< 0.1%
4.7158145361
< 0.1%
4.7158093211
< 0.1%
4.7157957051
< 0.1%
4.7157807171
< 0.1%
4.7157787411
< 0.1%
4.7157716041
< 0.1%
4.7157712191
< 0.1%
4.7157688041
< 0.1%
4.715711542
< 0.1%

g
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct286976
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.330310087
Minimum4.013674673
Maximum4.562757062
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-02-27T16:48:29.432804image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum4.013674673
5-th percentile4.170609414
Q14.261271438
median4.345223338
Q34.3996469
95-th percentile4.462257018
Maximum4.562757062
Range0.5490823884
Interquartile range (IQR)0.1383754618

Descriptive statistics

Standard deviation0.09190792226
Coefficient of variation (CV)0.02122432815
Kurtosis-0.3235412083
Mean4.330310087
Median Absolute Deviation (MAD)0.065361186
Skewness-0.4524174463
Sum1325702.782
Variance0.008447066174
MonotonicityNot monotonic
2022-02-27T16:48:29.526544image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.2406152035
 
< 0.1%
4.4356477285
 
< 0.1%
4.4296231945
 
< 0.1%
4.3762870494
 
< 0.1%
4.3516977914
 
< 0.1%
4.4442212574
 
< 0.1%
4.3177210554
 
< 0.1%
4.2711198784
 
< 0.1%
4.4081500924
 
< 0.1%
4.3778141064
 
< 0.1%
Other values (286966)306102
> 99.9%
ValueCountFrequency (%)
4.0136746731
< 0.1%
4.0138896451
< 0.1%
4.0139921631
< 0.1%
4.014009041
< 0.1%
4.014081281
< 0.1%
4.0142269091
< 0.1%
4.014266551
< 0.1%
4.0148842441
< 0.1%
4.0149326131
< 0.1%
4.0150264011
< 0.1%
ValueCountFrequency (%)
4.5627570621
< 0.1%
4.5594223691
< 0.1%
4.5583797511
< 0.1%
4.5569742011
< 0.1%
4.5534478731
< 0.1%
4.5533720551
< 0.1%
4.5531220831
< 0.1%
4.5529716971
< 0.1%
4.5524610581
< 0.1%
4.5523665571
< 0.1%

r
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct284109
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.219469719
Minimum3.942790444
Maximum4.45792328
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-02-27T16:48:29.620304image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3.942790444
5-th percentile4.086180072
Q14.153134489
median4.223216789
Q34.276857071
95-th percentile4.356139823
Maximum4.45792328
Range0.5151328355
Interquartile range (IQR)0.123722582

Descriptive statistics

Standard deviation0.08424142608
Coefficient of variation (CV)0.01996493202
Kurtosis-0.4763943135
Mean4.219469719
Median Absolute Deviation (MAD)0.06113866736
Skewness-0.08483506413
Sum1291769.557
Variance0.007096617868
MonotonicityNot monotonic
2022-02-27T16:48:29.714054image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.2273646455
 
< 0.1%
4.2714489094
 
< 0.1%
4.2413985384
 
< 0.1%
4.2095502184
 
< 0.1%
4.134378514
 
< 0.1%
4.2520709764
 
< 0.1%
4.1297793014
 
< 0.1%
4.1371255874
 
< 0.1%
4.2494676414
 
< 0.1%
4.2442220184
 
< 0.1%
Other values (284099)306104
> 99.9%
ValueCountFrequency (%)
3.9427904441
< 0.1%
3.9429145571
< 0.1%
3.9431781331
< 0.1%
3.9432883331
< 0.1%
3.9433008061
< 0.1%
3.944381061
< 0.1%
3.9445201221
< 0.1%
3.9445582591
< 0.1%
3.9446825011
< 0.1%
3.9448582581
< 0.1%
ValueCountFrequency (%)
4.457923281
< 0.1%
4.4563063751
< 0.1%
4.4555905811
< 0.1%
4.4527847861
< 0.1%
4.4507551811
< 0.1%
4.4502271721
< 0.1%
4.4500920041
< 0.1%
4.4495859371
< 0.1%
4.4474667921
< 0.1%
4.4473395651
< 0.1%

i
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct281774
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.171296928
Minimum3.90566773
Maximum4.401652855
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-02-27T16:48:29.889022image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3.90566773
5-th percentile4.046734283
Q14.111284847
median4.175939306
Q34.225626536
95-th percentile4.294732176
Maximum4.401652855
Range0.4959851249
Interquartile range (IQR)0.1143416891

Descriptive statistics

Standard deviation0.07738981046
Coefficient of variation (CV)0.01855293732
Kurtosis-0.4304253826
Mean4.171296928
Median Absolute Deviation (MAD)0.05671445537
Skewness-0.1658049424
Sum1277021.698
Variance0.005989182763
MonotonicityNot monotonic
2022-02-27T16:48:29.982773image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.0781100654
 
< 0.1%
4.13450374
 
< 0.1%
4.1893931094
 
< 0.1%
4.2187679184
 
< 0.1%
4.1201079594
 
< 0.1%
4.1424756054
 
< 0.1%
4.0843643414
 
< 0.1%
4.1912979644
 
< 0.1%
4.2029574754
 
< 0.1%
4.0826589094
 
< 0.1%
Other values (281764)306105
> 99.9%
ValueCountFrequency (%)
3.905667731
< 0.1%
3.9059996971
< 0.1%
3.9062106371
< 0.1%
3.9063797911
< 0.1%
3.9068511611
< 0.1%
3.9069107931
< 0.1%
3.9069168521
< 0.1%
3.9069243541
< 0.1%
3.9069776361
< 0.1%
3.9070499571
< 0.1%
ValueCountFrequency (%)
4.4016528551
< 0.1%
4.4016247331
< 0.1%
4.4000133541
< 0.1%
4.3997444341
< 0.1%
4.3995362341
< 0.1%
4.3977996771
< 0.1%
4.3975972191
< 0.1%
4.3974991971
< 0.1%
4.3973312711
< 0.1%
4.3966324531
< 0.1%

z
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct281089
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.141787799
Minimum3.876660841
Maximum4.372613596
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 MiB
2022-02-27T16:48:30.076523image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3.876660841
5-th percentile4.017535909
Q14.08318128
median4.146012822
Q34.19528822
95-th percentile4.264935707
Maximum4.372613596
Range0.4959527553
Interquartile range (IQR)0.1121069402

Descriptive statistics

Standard deviation0.07701498271
Coefficient of variation (CV)0.01859462301
Kurtosis-0.3743906179
Mean4.141787799
Median Absolute Deviation (MAD)0.05575259366
Skewness-0.1558285645
Sum1267987.626
Variance0.005931307562
MonotonicityNot monotonic
2022-02-27T16:48:30.170273image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.0782923325
 
< 0.1%
4.1156177624
 
< 0.1%
4.1388717144
 
< 0.1%
4.1589561964
 
< 0.1%
4.1282618054
 
< 0.1%
4.262996764
 
< 0.1%
4.1661258764
 
< 0.1%
4.1708191954
 
< 0.1%
4.1505575654
 
< 0.1%
4.071127494
 
< 0.1%
Other values (281079)306104
> 99.9%
ValueCountFrequency (%)
3.8766608411
< 0.1%
3.8766785191
< 0.1%
3.8767195731
< 0.1%
3.8767741781
< 0.1%
3.876937981
< 0.1%
3.8769705811
< 0.1%
3.8771864961
< 0.1%
3.8771872821
< 0.1%
3.8775257681
< 0.1%
3.8775260631
< 0.1%
ValueCountFrequency (%)
4.3726135961
< 0.1%
4.3724285391
< 0.1%
4.3723254481
< 0.1%
4.3721565861
< 0.1%
4.3720137631
< 0.1%
4.3718149011
< 0.1%
4.3717852851
< 0.1%
4.3717529511
< 0.1%
4.3716720441
< 0.1%
4.371636711
< 0.1%

uErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct306145
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.751966378
Minimum-5.989450365
Maximum0.4284759332
Zeros0
Zeros (%)0.0%
Negative295383
Negative (%)96.5%
Memory size2.3 MiB
2022-02-27T16:48:30.264023image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-5.989450365
5-th percentile-3.903257992
Q1-2.497533178
median-1.597732965
Q3-0.9058569665
95-th percentile-0.1079462242
Maximum0.4284759332
Range6.417926298
Interquartile range (IQR)1.591676211

Descriptive statistics

Standard deviation1.1436446
Coefficient of variation (CV)-0.6527777097
Kurtosis-0.01439868754
Mean-1.751966378
Median Absolute Deviation (MAD)0.7775894641
Skewness-0.5770173508
Sum-536355.7468
Variance1.307922971
MonotonicityNot monotonic
2022-02-27T16:48:30.370120image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.67729931
 
< 0.1%
-0.70708394111
 
< 0.1%
-1.1525415641
 
< 0.1%
-0.83460476451
 
< 0.1%
-2.1394149221
 
< 0.1%
-3.0407384351
 
< 0.1%
-3.2511634271
 
< 0.1%
-1.4361342381
 
< 0.1%
-2.7133214261
 
< 0.1%
-2.1754530211
 
< 0.1%
Other values (306135)306135
> 99.9%
ValueCountFrequency (%)
-5.9894503651
< 0.1%
-5.9640884091
< 0.1%
-5.9507618851
< 0.1%
-5.93892591
< 0.1%
-5.9244619411
< 0.1%
-5.9231474531
< 0.1%
-5.893122761
< 0.1%
-5.8837109431
< 0.1%
-5.8777585031
< 0.1%
-5.8749231881
< 0.1%
ValueCountFrequency (%)
0.42847593321
< 0.1%
0.42846370091
< 0.1%
0.42841744911
< 0.1%
0.42830425821
< 0.1%
0.42814573071
< 0.1%
0.42769986111
< 0.1%
0.42741173531
< 0.1%
0.42739824431
< 0.1%
0.42738746281
< 0.1%
0.42721704111
< 0.1%

gErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct306145
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.807537702
Minimum-5.463659632
Maximum-1.59098666
Zeros0
Zeros (%)0.0%
Negative306145
Negative (%)100.0%
Memory size2.3 MiB
2022-02-27T16:48:30.456310image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-5.463659632
5-th percentile-4.936135378
Q1-4.46546238
median-3.833972921
Q3-3.244591631
95-th percentile-2.4679411
Maximum-1.59098666
Range3.872672973
Interquartile range (IQR)1.220870749

Descriptive statistics

Standard deviation0.7771950596
Coefficient of variation (CV)-0.2041201218
Kurtosis-0.6418518422
Mean-3.807537702
Median Absolute Deviation (MAD)0.6106850307
Skewness0.3022734045
Sum-1165658.63
Variance0.6040321606
MonotonicityNot monotonic
2022-02-27T16:48:30.550060image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.2318634461
 
< 0.1%
-3.3374690491
 
< 0.1%
-4.0305988651
 
< 0.1%
-3.774322981
 
< 0.1%
-4.2937981561
 
< 0.1%
-4.6745379241
 
< 0.1%
-4.7129739361
 
< 0.1%
-3.8685273621
 
< 0.1%
-4.4117171331
 
< 0.1%
-4.7384678161
 
< 0.1%
Other values (306135)306135
> 99.9%
ValueCountFrequency (%)
-5.4636596321
< 0.1%
-5.4529902471
< 0.1%
-5.4357936091
< 0.1%
-5.4349973191
< 0.1%
-5.4331831921
< 0.1%
-5.4276787511
< 0.1%
-5.4225830481
< 0.1%
-5.4211952551
< 0.1%
-5.4175624911
< 0.1%
-5.4174378921
< 0.1%
ValueCountFrequency (%)
-1.590986661
< 0.1%
-1.5912689991
< 0.1%
-1.5913740341
< 0.1%
-1.5914684971
< 0.1%
-1.5915846031
< 0.1%
-1.5922324211
< 0.1%
-1.5923618391
< 0.1%
-1.5924725981
< 0.1%
-1.5930020021
< 0.1%
-1.5932190881
< 0.1%

rErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct306145
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.902248231
Minimum-4.842348093
Maximum-2.316442643
Zeros0
Zeros (%)0.0%
Negative306145
Negative (%)100.0%
Memory size2.3 MiB
2022-02-27T16:48:30.659436image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-4.842348093
5-th percentile-4.450022644
Q1-4.225098603
median-3.988030438
Q3-3.660414959
95-th percentile-3.051790652
Maximum-2.316442643
Range2.52590545
Interquartile range (IQR)0.5646836446

Descriptive statistics

Standard deviation0.4295883677
Coefficient of variation (CV)-0.1100874015
Kurtosis0.4341478198
Mean-3.902248231
Median Absolute Deviation (MAD)0.2695475933
Skewness0.8770298958
Sum-1194653.785
Variance0.1845461657
MonotonicityNot monotonic
2022-02-27T16:48:30.753186image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.2813399441
 
< 0.1%
-3.6826389071
 
< 0.1%
-4.1460661451
 
< 0.1%
-3.9518825551
 
< 0.1%
-4.1033354321
 
< 0.1%
-4.135454491
 
< 0.1%
-4.1978810941
 
< 0.1%
-4.0355373551
 
< 0.1%
-4.0922984711
 
< 0.1%
-4.3678792251
 
< 0.1%
Other values (306135)306135
> 99.9%
ValueCountFrequency (%)
-4.8423480931
< 0.1%
-4.8219909731
< 0.1%
-4.8191912211
< 0.1%
-4.8030893441
< 0.1%
-4.800802861
< 0.1%
-4.7990788211
< 0.1%
-4.798171881
< 0.1%
-4.7962936421
< 0.1%
-4.7928279071
< 0.1%
-4.7923738821
< 0.1%
ValueCountFrequency (%)
-2.3164426431
< 0.1%
-2.3167229621
< 0.1%
-2.3170209711
< 0.1%
-2.3170790641
< 0.1%
-2.3171552861
< 0.1%
-2.3172540581
< 0.1%
-2.3181136631
< 0.1%
-2.3183077081
< 0.1%
-2.3185022571
< 0.1%
-2.3191405671
< 0.1%

iErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct306145
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.711891984
Minimum-4.687352277
Maximum-2.148897138
Zeros0
Zeros (%)0.0%
Negative306145
Negative (%)100.0%
Memory size2.3 MiB
2022-02-27T16:48:30.846924image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-4.687352277
5-th percentile-4.143779386
Q1-3.945210513
median-3.759195075
Q3-3.52501356
95-th percentile-3.118581491
Maximum-2.148897138
Range2.538455139
Interquartile range (IQR)0.4201969528

Descriptive statistics

Standard deviation0.3174215623
Coefficient of variation (CV)-0.08551476274
Kurtosis0.6435866523
Mean-3.711891984
Median Absolute Deviation (MAD)0.2051619909
Skewness0.7740167841
Sum-1136377.171
Variance0.1007564482
MonotonicityNot monotonic
2022-02-27T16:48:31.004473image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.1653682711
 
< 0.1%
-3.4772809331
 
< 0.1%
-3.9140144081
 
< 0.1%
-3.6949494791
 
< 0.1%
-3.841833131
 
< 0.1%
-3.7774327241
 
< 0.1%
-3.8515805021
 
< 0.1%
-3.8543928351
 
< 0.1%
-3.772934841
 
< 0.1%
-4.0457745471
 
< 0.1%
Other values (306135)306135
> 99.9%
ValueCountFrequency (%)
-4.6873522771
< 0.1%
-4.5495908391
< 0.1%
-4.5389460811
< 0.1%
-4.5351952671
< 0.1%
-4.5234701811
< 0.1%
-4.5183749331
< 0.1%
-4.5137285941
< 0.1%
-4.5109631311
< 0.1%
-4.5070719591
< 0.1%
-4.5069505891
< 0.1%
ValueCountFrequency (%)
-2.1488971381
< 0.1%
-2.1494120921
< 0.1%
-2.1498660651
< 0.1%
-2.1519167941
< 0.1%
-2.1528018711
< 0.1%
-2.1590044971
< 0.1%
-2.1593442291
< 0.1%
-2.1599444651
< 0.1%
-2.1607556291
< 0.1%
-2.1612106691
< 0.1%

zErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct306145
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.206814261
Minimum-4.481989388
Maximum-1.372695403
Zeros0
Zeros (%)0.0%
Negative306145
Negative (%)100.0%
Memory size2.3 MiB
2022-02-27T16:48:31.113906image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-4.481989388
5-th percentile-3.734217329
Q1-3.470269867
median-3.247003498
Q3-2.986478027
95-th percentile-2.535875488
Maximum-1.372695403
Range3.109293985
Interquartile range (IQR)0.4837918401

Descriptive statistics

Standard deviation0.3682715594
Coefficient of variation (CV)-0.1148403149
Kurtosis0.5489950257
Mean-3.206814261
Median Absolute Deviation (MAD)0.2393219266
Skewness0.6215566459
Sum-981750.1518
Variance0.1356239414
MonotonicityNot monotonic
2022-02-27T16:48:31.200838image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.7285212151
 
< 0.1%
-2.7282445311
 
< 0.1%
-3.2715597941
 
< 0.1%
-3.0422595711
 
< 0.1%
-3.1550695241
 
< 0.1%
-2.9704926481
 
< 0.1%
-3.0898885231
 
< 0.1%
-3.1937899091
 
< 0.1%
-3.0337867071
 
< 0.1%
-3.408514221
 
< 0.1%
Other values (306135)306135
> 99.9%
ValueCountFrequency (%)
-4.4819893881
< 0.1%
-4.4529662111
< 0.1%
-4.3528736111
< 0.1%
-4.3497405851
< 0.1%
-4.3450570471
< 0.1%
-4.3440886791
< 0.1%
-4.3401471131
< 0.1%
-4.3400520031
< 0.1%
-4.3394664911
< 0.1%
-4.3387483191
< 0.1%
ValueCountFrequency (%)
-1.3726954031
< 0.1%
-1.372966651
< 0.1%
-1.3740022871
< 0.1%
-1.3762869641
< 0.1%
-1.3764830341
< 0.1%
-1.3794439371
< 0.1%
-1.3812745061
< 0.1%
-1.3874116711
< 0.1%
-1.3968558071
< 0.1%
-1.4015115051
< 0.1%

Interactions

2022-02-27T16:48:26.746032image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:10.776634image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:12.582917image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:14.371661image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:16.076384image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:17.865830image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:19.572991image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:21.395072image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:23.234864image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:24.958203image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:26.915467image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:10.959443image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:12.748307image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:14.538789image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:16.245040image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:18.033920image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:19.820779image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:21.577777image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:23.418047image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:25.125410image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:27.096766image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:11.125700image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:12.915539image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:14.705902image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:16.430370image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:18.215987image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:19.988813image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:21.746844image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:23.587130image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:25.369812image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:27.266791image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:11.357925image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:13.100136image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:14.872059image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:16.597766image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:18.383449image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:20.158028image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:21.932952image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:23.756932image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:25.527128image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:27.434273image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:11.543613image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:13.268062image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:15.041554image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:16.763277image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:18.550505image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:20.324797image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:22.112898image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:23.922038image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:25.711118image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:27.615235image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:11.710187image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:13.435849image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:15.222438image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:16.991694image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:18.722066image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:20.508461image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:22.281207image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:24.089301image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:25.880294image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:27.784956image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:11.880158image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:13.616608image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:15.392689image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:17.165236image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:18.887034image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:20.678169image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:22.526727image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:24.258696image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:26.044248image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:27.968083image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:12.064495image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:13.786351image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:15.573724image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:17.358934image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:19.070449image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:20.878263image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:22.700780image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:24.438607image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:26.230537image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:28.197669image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:12.229658image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:13.954405image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:15.741752image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:17.515910image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:19.240025image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:21.044185image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:22.887260image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:24.607995image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:26.396984image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:28.370304image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:12.399433image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:14.197946image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:15.907958image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:17.697816image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:19.406104image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:21.212046image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:23.051690image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:24.788724image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:48:26.564100image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2022-02-27T16:48:31.278976image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-02-27T16:48:31.388351image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-02-27T16:48:31.494570image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-02-27T16:48:31.603945image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-02-27T16:48:28.510749image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
A simple visualization of nullity by column.
2022-02-27T16:48:28.736821image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

ugrizuErrgErrrErriErrzErr
04.4837464.3434814.2414044.2041404.182654-1.677299-4.231863-4.281340-4.165368-3.728521
14.4916654.3890354.2776104.2367444.204361-0.881700-3.113318-3.658649-3.648646-3.193702
24.5032844.4363344.3137004.2640864.235675-0.918657-2.707566-3.497811-3.502225-3.154995
34.3945404.2377164.1343744.0987174.072904-2.477287-4.627525-4.349149-4.081926-3.754782
44.4313734.3374834.2091274.1678794.138687-1.959126-3.886534-4.157697-3.983670-3.705842
54.4036684.2578154.1431184.1066674.083163-1.899961-4.175228-4.078067-3.835319-3.452655
64.5745334.4767734.3582604.3111234.284871-0.462633-2.322977-3.337323-3.415510-2.993526
74.4524924.3491014.2367464.1974574.165483-1.511520-3.716447-4.025638-3.918315-2.634167
84.4645254.3493704.2496434.2162294.193434-1.545325-3.933293-4.104074-3.942459-3.650699
94.4189174.3398744.2430644.2085244.186363-2.029290-3.771700-3.927089-3.782695-3.474072

Last rows

ugrizuErrgErrrErriErrzErr
3061354.5220914.4253104.3163424.2506614.209480-0.503946-2.837633-3.151667-3.092734-2.847622
3061364.5488194.4734554.3561534.2928154.259143-0.569692-2.391060-3.136930-3.116880-2.890001
3061374.6233204.4783544.3725354.3111714.280582-0.657245-2.679417-3.272047-3.309023-2.980389
3061384.6050704.4208074.2862404.2331904.1982470.068238-3.128750-3.671060-3.490849-3.290587
3061394.5519974.4081684.2763294.2241044.186736-0.058089-3.010925-3.603465-3.423200-3.099019
3061404.4772644.3714944.3128264.2577644.229376-0.474360-2.918404-2.514621-2.421791-2.055913
3061414.6747604.4117144.2763984.2156444.180888-0.144703-2.199854-2.717175-2.590172-2.366846
3061424.7015644.4491684.3376474.2711674.239775-1.055403-2.323258-2.815455-2.846164-2.508469
3061434.6920454.4605994.3454654.2810254.236006-1.276604-2.177615-2.765151-2.827652-2.648325
3061444.4587514.4392114.3250404.2558614.213431-1.525927-2.891918-3.258731-3.316571-3.022117